Diversity of α-helical host defense peptides (αHDPs) contributes to immunity against a broad spectrum of pathogens via multiple functions. Thus, resolving common structure-function relationships among αHDPs is inherently difficult, even for artificial-intelligencebased methods that seek multifactorial trends rather than foundational principles. Here, bioinformatic and pattern recognition methods were applied to identify a unifying signature of eukaryotic αHDPs derived from amino acid sequence, biochemical, and threedimensional properties of known αHDPs. The signature formula contains a helical domain of 12 residues with a mean hydrophobic moment of 0.50 and favoring aliphatic over aromatic hydrophobes in 18-aa windows of peptides or proteins matching its semantic definition. The holistic α-core signature subsumes existing physicochemical properties of αHDPs, and converged strongly with predictions of an independent machine-learning-based classifier recognizing sequences inducing negative Gaussian curvature in target membranes. Queries using the α-core formula identified 93% of all annotated αHDPs in proteomic databases and retrieved all major αHDP families. Synthesis and antimicrobial assays confirmed efficacies of predicted sequences having no previously known antimicrobial activity. The unifying α-core signature establishes a foundational framework for discovering and understanding αHDPs encompassing diverse structural and mechanistic variations, and affords possibilities for deterministic design of antiinfectives.antimicrobial | host defense | antiinfective | amphipathic | bioinformatics A ntimicrobial host defense peptides (HDPs) are an evolutionarily ancient arm of host immunity that first arose in prokaryotes as a means to counter microbial competitors. Subsequently, such peptides evolved through adaptive radiation to exist in all classes of eukaryotes, where they continue to act in firstline defense against infection (1). Extensive studies have established that such peptides are not indiscriminant detergents, but rather have complex and multimodal mechanisms of action (2-4).As a group, α-helical HDPs (αHDPs) are among the most rapidly evolving molecules characterized to date. Moreover, genes encoding αHDPs are under strong positive selection, affording a high degree of mutational tolerance despite being limited by the biophysical constraints of an amphipathic helix (5-8). When compounded over an evolutionary timescale, this process has generated an exceptionally diverse repertoire of peptides capable of exerting multiple antimicrobial mechanisms. However, such diversity and context-dependent activity have also presented challenges to identifying common αHDP structure-activity relationships (SARs). While a number of groups have used computational or quantitative SAR (QSAR) methods, these efforts have largely focused on drug candidate optimization (9-12). As a result, other than charge or amphipathicity, resolving the unifying physicochemical requisites in three-dimensional space that confer antimicrobial ac...